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This study investigated the accuracy and physical representation of air-sea surface heat flux estimates for the Indian Ocean on annual, seasonal, and interannual time scales. Six heat flux products were analyzed, including the newly developed latent and sensible heat fluxes from the Objectively Analyzed Air-Sea Heat Fluxes (OAFlux) project and net shortwave and longwave radiation results from the International Satellite Cloud Climatology Project (ISCCP), the heat flux analysis from the Southampton Oceanography Centre (SOC), the National Centers for Environmental Prediction reanalysis 1 (NCEP1) and reanalysis-2 (NCEP2) datasets, and the European Centre for Medium-Range Weather Forecasts operational (ECMWF-OP) and 40-yr Re-Analysis (ERA-40) products.This paper presents the analysis of the six products in depicting the mean, the seasonal cycle, and the interannual variability of the net heat flux into the ocean. Two time series of in situ flux measurements, one taken from a 1-yr Arabian Sea Experiment field program and the other from a 1-month Joint Air-Sea Monsoon Interaction Experiment (JASMINE) field program in the Bay of Bengal were used to evaluate the statistical properties of the flux products over the measurement periods. The consistency between the six products on seasonal and interannual time scales was investigated using a standard deviation analysis and a physically based correlation analysis.The study has three findings. First of all, large differences exist in the mean value of the six heat flux products. Part of the differences may be attributable to the bias in the numerical weather prediction (NWP) models that underestimates the net heat flux into the Indian Ocean. Along the JASMINE ship tracks, the four NWP modeled mean fluxes all have a sign opposite to the observations, with NCEP1 being underestimated by 53 W m Ϫ2 (the least biased) and ECMWF-OP by 108 W m Ϫ2 (the most biased). At the Arabian Sea buoy site, the NWP mean fluxes also have an underestimation bias, with the smallest bias of 26 W m Ϫ2 (ERA-40) and the largest bias of 69 W m Ϫ2 (NCEP1). On the other hand, the OAFluxϩISCCP has the best comparison at both measurement sites. Second, the bias effect changes with the time scale. Despite the fact that the mean is biased significantly, there is no major bias in the seasonal cycle of all the products except for ECMWF-OP. The latter does not have a fixed mean due to the frequent updates of the model platform. Finally, among the four products (OAFluxϩISCCP, ERA-40, NCEP1, and NCEP2) that can be used for studying interannual variability, OAFluxϩISCCP and ERA-40 Q net have good consistency as judged from both statistical and physical measures. NCEP1 shows broad agreement with the two products, with varying details. By comparison, NCEP2 is the least representative of the Q net variabilities over the basin scale.

The present study used a new net surface heat flux (Q net ) product obtained from the Objective Analyzed Air-Sea Fluxes (OAFlux) project and the International Satellite Cloud Climatology Project (ISCCP) to examine two specific issues-one is to which degree Q net controls seasonal variations of sea surface temperature (SST) in the tropical Atlantic Ocean (20°S-20°N, east of 60°W), and the other is whether the physical relation can serve as a measure to evaluate the physical representation of a heat flux product. To better address the two issues, the study included the analysis of three additional heat flux products: the Southampton Oceanographic Centre (SOC) heat flux analysis based on ship reports, and the model fluxes from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40). The study also uses the monthly subsurface temperature fields from the World Ocean Atlas to help analyze the seasonal changes of the mixed layer depth (h MLD ).The study showed that the tropical Atlantic sector could be divided into two regimes based on the influence level of Q net . SST variability poleward of 5°S and 10°N is dominated by the annual cycle of Q net . In these regions the warming (cooling) of the sea surface is highly correlated with the increased (decreased) Q net confined in a relatively shallow (deep) h MLD . The seasonal evolution of SST variability is well predicted by simply relating the local Q net with a variable h MLD . On the other hand, the influence of Q net diminishes in the deep Tropics within 5°S and 10°N and ocean dynamic processes play a dominant role. The dynamicsinduced changes in SST are most evident along the two belts, one of which is located on the equator and the other off the equator at about 3°N in the west, which tilts to about 10°N near the northwestern African coast.The study also showed that if the degree of consistency between the correlation relationships of Q net , h MLD , and SST variability serves as a measure of the quality of the Q net product, then the Q net from OAFlux ϩ ISCCP and ERA-40 are most physically representative, followed by SOC. The NCEP-NCAR Q net is least representative. It should be noted that the Q net from OAFlux ϩ ISCCP and ERA-40 have a quite different annual mean pattern. OAFlux ϩ ISCCP agrees with SOC in that the tropical Atlantic sector gains heat from the atmosphere on the annual mean basis, where the ERA-40 and the NCEP-NCAR model reanalyses indicate that positive Q net occurs only in the narrow equatorial band and in the eastern portion of the tropical basin. Nevertheless, seasonal variances of the Q net from OAFlux ϩ ISCCP and ERA-40 are very similar once the respective mean is removed, which explains why the two agree with each other in accounting for the seasonal variability of SST.In summary, the study suggests that an accurate estimation of surface heat flux is crucially important for understandin...

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